Metadata-Version: 2.4
Name: data-automation-kit
Version: 2.0.6
Summary: A comprehensive Python package for automated data loading, cleaning, visualization, and quality checks with AI integration
Home-page: https://github.com/bellonbits/data-automation-kit
Author: Peter Gatitu
Author-email: petergatitu61@gmail.com
Keywords: data-analysis,automation,data-cleaning,visualization,data-quality,ai,machine-learning
Classifier: Development Status :: 4 - Beta
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Classifier: Topic :: Scientific/Engineering :: Information Analysis
Classifier: Topic :: Software Development :: Libraries :: Python Modules
Requires-Python: >=3.7
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: pandas>=1.3.0
Requires-Dist: numpy>=1.21.0
Requires-Dist: matplotlib>=3.5.0
Requires-Dist: seaborn>=0.11.0
Requires-Dist: sqlalchemy>=1.4.0
Requires-Dist: openpyxl>=3.0.0
Requires-Dist: groq>=0.3.0
Requires-Dist: scikit-learn>=1.0.0
Requires-Dist: scipy>=1.7.0
Dynamic: author
Dynamic: author-email
Dynamic: classifier
Dynamic: description
Dynamic: description-content-type
Dynamic: home-page
Dynamic: keywords
Dynamic: license-file
Dynamic: requires-dist
Dynamic: requires-python
Dynamic: summary

# Modern Analytics Helper - Data Automation Kit

A comprehensive, AI-powered data analysis toolkit that provides flexible analytics with interactive features.

## Features

- **Flexible Target Variables**: Choose any column as target, let AI suggest, or use unsupervised analysis
- **Selective Chart Visualization**: Choose exactly which visualizations to create
- **Interactive AI Q&A**: Ask any questions about your data and get AI-powered insights
- **Multiple Analysis Modes**: Quick, Guided, Custom, and AI Chat modes
- **Smart Data Cleaning**: Automated data quality assessment and cleaning
- **Professional Reporting**: Comprehensive analysis reports with actionable insights

## Quick Start

```python
from data_automation_kit import quick_analyze

# Start interactive analysis session
quick_analyze()
Or from command line:

bash
analyze-data
Installation
bash
pip install data-automation-kit
Usage Examples
Basic Analysis
python
from data_automation_kit import InteractiveAnalyzer

analyzer = InteractiveAnalyzer()
analyzer.start_interactive_session()
Custom Analysis
python
from data_automation_kit import DataLoader, AutoVisualizer

# Load your data
loader = DataLoader()
data = loader.load_csv("your_data.csv")

# Create visualizations
visualizer = AutoVisualizer(data)
plots = visualizer.create_comprehensive_visualizations()
Analysis Modes
Quick Analysis: Fully automated analysis with sample data

Guided Analysis: Step-by-step guided analysis with expert choices

Custom Analysis: Complete control over each analysis step

AI Chat Mode: Interactive Q&A about your data

Supported Data Sources
CSV Files

Excel Files

JSON Files

SQL Databases

Sample Datasets (Sales, Customers, Products, etc.)

Requirements
Python 3.7+

See requirements.txt for full dependencies

License
MIT License
